| 000 -LEADER |
|---|
| fixed length control field |
02049cam a22003258i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20230414151714.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
191130s2020 enk b 001 0 eng |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781108470049 |
| Qualifying information |
(hardback) |
|
|---|
| International Standard Book Number |
9781108455145 |
| Qualifying information |
(paperback) |
|
|---|
| Canceled/invalid ISBN |
9781108679930 |
| Qualifying information |
(epub) |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
LBSOR/DLC |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
DLC |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Deisenroth, Marc Peter |
| 9 (RLIN) |
6994 |
|
|---|
| Personal name |
Faisal, A. Aldo |
| 9 (RLIN) |
6996 |
|
|---|
| Personal name |
Ong, Cheng Soon |
| 9 (RLIN) |
6997 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Mathematics for machine learning |
| 263 ## - PROJECTED PUBLICATION DATE |
|---|
| Projected publication date |
1912 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Cambridge ; |
| -- |
New York, NY : |
| Name of producer, publisher, distributor, manufacturer |
Cambridge University Press, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2020. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
pages cm |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Media type code |
n |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Carrier type code |
nc |
| Source |
rdacarrier |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
"The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability, and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models, and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts"-- |
| Assigning source |
Provided by publisher. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning |
| General subdivision |
Mathematics. |
| 9 (RLIN) |
6995 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Book Home |
| Uniform Resource Identifier |
<a href="https://mml-book.github.io/">https://mml-book.github.io/</a> |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
7 |
| b |
cbc |
| c |
orignew |
| d |
1 |
| e |
ecip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Monography |
